Insights
AI Literacy as a Governance Control
AI literacy becomes a governance control when learning is tied to roles, risk, assigned responsibilities, and evidence of competence.
Testing Generative AI Outputs in Internal Audit
A practical approach to designing test cases, assessing consistency and refusals, sampling outputs, and documenting GenAI audit evidence.
AI Bias: What Auditors Can Actually Test
A practical boundary between governance and outcome testing that auditors can perform and specialist statistical fairness validation.
What Boards Should Ask Internal Audit About AI
Nine questions boards can use to assess whether Internal Audit understands AI exposure, covers material risks, and has the capability to provide assurance.
Building a Prompt Library for Auditors
A governed prompt library turns individual AI experimentation into a tested, versioned, reusable capability for internal audit.
Designing an AI Operating Model for Internal Audit
An AI operating model connects mandate, governance, people, methodology, data, tools, controls, and support so Internal Audit can scale responsibly.